We extract flight schedules, dynamic pricing, seat availability, and fare classes from Finnair. Delivered as clean JSON, CSV, or Parquet to S3, BigQuery, or Snowflake on your cadence.
Structured, schema-consistent data across all major object types — delivered clean, typed, and ready to query.
Complete list of extractable fields for Flight Schedules objects from finnair.com. All fields typed and schema-versioned.
"flight_number": "AY1331", "origin": "HEL", "destination": "LHR", "departure_time": "2024-05-12T08:00:00Z", "arrival_time": "2024-05-12T09:10:00Z", "duration_minutes": 190, "aircraft_type": "Airbus A350-900", "operated_by": "Finnair"
| # | flight_number | origin | destination | departure_time | arrival_time | duration_minutes |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
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Complete list of extractable fields for Pricing & Fares objects from finnair.com. All fields typed and schema-versioned.
"flight_number": "AY1331", "fare_class": "Economy Classic", "price": 214.5, "currency": "EUR", "taxes": 45.0, "finnair_plus_points": 1500, "refundable": false, "change_fee": 50.0
| # | flight_number | departure_date | fare_class | price | currency | taxes |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Seat Availability objects from finnair.com. All fields typed and schema-versioned.
"flight_number": "AY1331", "cabin_class": "Business", "seats_remaining": 4, "pitch_inches": 78, "width_inches": 21, "wifi_available": true, "power_outlets": true
| # | flight_number | date | cabin_class | seats_remaining | seat_map_url | pitch_inches |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
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Complete list of extractable fields for Route Network objects from finnair.com. All fields typed and schema-versioned.
"origin_airport": "HEL", "destination_airport": "JFK", "distance_km": 6604, "direct_flights_per_week": 7, "codeshare_partners": "['AA', 'BA', 'IB']", "terminal_origin": "2", "terminal_destination": "8"
| # | origin_airport | destination_airport | distance_km | direct_flights_per_week | codeshare_partners | seasonality |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
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Complete list of extractable fields for Baggage & Ancillaries objects from finnair.com. All fields typed and schema-versioned.
"fare_class": "Economy Light", "cabin_bag_allowance": "8kg", "checked_bag_allowance": "0kg", "extra_bag_price": 36.0, "meal_included": false, "lounge_access_price": 48.0
| # | fare_class | cabin_bag_allowance | checked_bag_allowance | extra_bag_price | sports_equipment_fee | pet_in_cabin_fee |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Our Finnair scraper handles every layer of the platform: flight schedules, dynamic pricing, seat availability, and ancillary fees - with JavaScript rendering, session management, and anti-bot circumvention built in.
Origin, destination, departure, arrival, aircraft type, and operating carrier for all Finnair and codeshare flights.
Capture base fares, taxes, and total prices across Light, Classic, and Flex ticket types.
Extract Avios pricing and tier point accrual rates for specific routes and fare classes.
Track remaining seats per cabin class to build demand forecasting models.
Extract seat pitch, Wi-Fi availability, and power outlet data for specific tail numbers and aircraft types.
Scrape pricing in EUR, USD, GBP, and 20+ other local currencies directly from the booking engine.
Identify codeshare flights operated by British Airways, American Airlines, and other partners.
Map minimum connection times and layover durations at Helsinki Airport (HEL).
Track dynamic pricing for extra baggage, seat selection, and lounge access.
Run hourly sweeps on high-value routes or daily catalogue updates for the entire network.
Brief in. Clean data out.
Provide route pairs, date ranges, and cabin classes. We design the extraction schema together.
We configure Scrapy / Playwright crawlers, proxy rotation, and session management for finnair.com.
Schema validation, null-rate checks, and price-outlier detection before full launch.
JSON / CSV / Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
Airlines invest heavily in scraping detection. Here is how we stay resilient - and why teams choose managed infrastructure over DIY.
Airlines aggressively block scraper IPs. We use residential ISP proxies with realistic browser fingerprints and full cookie session management to bypass Akamai and Cloudflare protections.
Finnair's booking engine is a complex single-page application. We run full Playwright browser sessions to execute JavaScript, select dates, and hydrate pricing widgets.
Extracting final pricing requires navigating through search, flight selection, and passenger detail steps. Our crawlers maintain session state across the entire funnel.
Airline DOM structures update frequently. We use multiple fallback chains per field, including CSS selectors, XPath, and API interception, to ensure pipeline stability.
We maintain a hash index of last-seen values per route. Subsequent runs only push diffs, reducing compute cost and downstream processing load.
Airlines and OTAs monitor Finnair's dynamic pricing across routes to optimise their own revenue management systems.
Hedge funds and travel analysts track seat availability depletion rates to estimate load factors and quarterly revenue.
Aviation consultants analyse frequency changes and aircraft deployment on specific city pairs to identify market trends.
Points aggregators scrape Finnair Plus Avios pricing to find high-value redemption opportunities for users.
TMCs integrate direct schedule and pricing data to bypass GDS fees and offer better options to corporate clients.
Competitors track Finnair's pricing for bags, seats, and lounge access to adjust their own unbundled fare strategies.
"Finnair's booking engine holds the ground truth for Northern European and Asian flight connectivity, but extracting it requires navigating complex multi-step state machines."
Most teams underestimate the investment required to scrape airline booking engines. Reliable Finnair extraction requires handling Akamai bot protection, maintaining session cookies through multi-page search flows, and parsing dynamic JavaScript responses. DataFlirt absorbs that complexity so your engineers can focus on yield analysis, not infrastructure.
Everything supported by our finnair.com scraper — rendered SPA elements, auth walls, rate-limit evasion and beyond.
Open-source tooling on proven cloud infra — no vendor lock-in, full observability.
Scrapy handles crawl orchestration, deduplication, and retry logic. Playwright handles JavaScript rendering, cookie sessions, and interaction flows. Combined via scrapy-playwright middleware.
We maintain pools of residential ISP proxies. Rotation happens per-request with sticky sessions where required. IP score monitoring prevents blacklisted pool contamination.
Pipelines run on AWS Lambda (burst) and ECS (sustained). Airflow handles scheduling, dependency management, and SLA alerting. All state stored in managed Postgres.
Data delivered to where your team already works — no new tooling required.
About finnair.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available flight data is generally permissible. DataFlirt targets only public, non-authenticated schedules and pricing. We do not bypass authentication walls. Clients should review Finnair's terms and consult legal counsel.
We use residential ISP proxies and full Playwright browser sessions with realistic fingerprints. Our crawlers mimic human interaction patterns to bypass Akamai and Cloudflare.
Yes. We can configure the crawler to select specific regions and currencies before initiating the flight search, capturing exact local pricing.
We extract the remaining seat counts displayed during the booking flow.
We can configure pipelines to run at hourly intervals for high-priority routes, ensuring you capture dynamic pricing shifts as they happen.
Yes, we can scrape the points-plus-cash pricing options available on the public search results pages.
Our smallest packages start at a defined route list (typically 100-500 route pairs) with daily delivery. For larger networks, we price based on volume and frequency.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a one-off route network dump or a continuous price-monitoring feed across 5,000 city pairs, we scope, build, and operate the pipeline. Tell us what you need.
